Data envelopment analysis is a methodology to distinguish between efficient and inefficient units, which could be anything from industries to firms to branches to hedge funds to algotrading robots to platoons to cockroaches to galaxies etc etc. Initially born within dull and stern macro economic realms, DEA gradually evolved into KPI-like methodology applied to approximately anything, usually studied and researched under operation research umbrella.

The paper develops an algorithm for making long-term (up to three months ahead) predictions of volatility reversals based on long memory properties of financial time series. The approach for computing fractal dimension using sequence of the minimal covers with decreasing scale is used to decompose volatility into two dynamic components: specific and structural. We introduce two separate models for both, based on different principles and capable of catching long uptrends in volatility. To test statistical significance of its abilities we introduce several estimators of conditional and unconditional probabilities of reversals in observed and predicted dynamic components of volatility. Our results could be used for forecasting points of market transition to an unstable state.

Seventy Factorial is a company, placed in Moscow, Russia. We are a team of 5 developers, researchers, support and financial compliance specialists, with 50 years of relevant experience. We focus on developing software for trading, portfolio management and data analysis. We come from Bloomberg Laboratory placed at Financial University under the Government of the Russian Federation, mostly we are professors, graduates and students of the University.